CompressLLM Models.Deploy Anywhere.
Condense compresses large models into small, deployable networks — automatically.
Get StartedBig Models.
Bigger Problems.
Today's neural networks are too large, too slow, too expensive.
Latency
Models take too long to respond
Cost
GPU inference bills skyrocket
Hardware
Cannot deploy to edge devices
Distillation-as-a-Service
Upload your model. Choose your objective. Get a distilled, deployable version — automatically.
Export Formats
Upload Model
Provide your model or Hugging Face link
Choose Objective
Select target size, latency, or hardware
Distillation Runs
Automated distillation, pruning, quantization
Download Model
Get optimized model in your format
30 Seconds to Value
Install, compress, deploy. It's that simple.
Built for Production
Enterprise-grade compression with the simplicity of a service.
Custom Compression Pipelines
Tailor pruning, quantization, and distillation strategies to your specific needs.
Automatic Benchmarking
Real-time accuracy, latency, and throughput metrics for every compressed model.
Hosted Model Monitoring
Monitor accuracy and performance in one dashboard. Track drift and degradation.
CLI + SDK Interface
IncomingIntegrate distillation into your CI/CD. Python SDK for programmatic access.
Quantization Modules
INT8, INT4, and mixed-precision quantization with minimal accuracy loss.
GPU-Accelerated Jobs
Scale distillation workloads with on-demand GPU clusters. Fast iteration cycles.
Simple, Transparent Pricing
Buy tokens, run compression jobs. 1 token = 1 hour of compute.
Builder
Perfect for solo developers and small-scale model experiments.
Compression methods
- 15 compression tokens
- All compression types
- HuggingFace integration
Studio
For teams running regular compression pipelines in production.
Compression methods
- 40 compression tokens
- All compression types
- HuggingFace integration
- Priority support
Scale
High-volume compression for enterprise and research teams.
Compression methods
- 100 compression tokens
- All compression types
- HuggingFace integration
- Priority support
- Advanced benchmarking
Tokens never expire · Unused tokens roll over · Refunded on job failure
The Path Forward
Building the future of neural network compression.
- Knowledge Distillation
- HuggingFace Integration
- Multi-format Export
- Real-time Job Monitoring
- Post-Training Quantization
- Structured Pruning
- Python SDK & CLI
- Visual Pipeline Builder
- LoRA Compression
- Multi-Teacher Distillation
- Quantization-Aware Training
- Edge Device Optimization
- Multi-Modal Compression
- Neural Architecture Search
- Distributed Training
- On-Premise Deployment
Stay Updated.
Join the Community.
Get the latest updates on model compression research and features.